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Record W3157688902 · doi:10.1111/1753-6405.13097

Promoting cultural rigour through critical appraisal tools in First Nations peoples’ research

2021· article· en· W3157688902 on OpenAlexaboutno aff
Mark Lock, Troy Walker, Jennifer Browne

Bibliographic record

VenueAustralian and New Zealand Journal of Public Health · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsnot available
Fundersnot available
KeywordsRigourCritical appraisalPoliticsPublic healthEthosSociologyCultural safetyHuman rightsPeer reviewEngineering ethicsSocial sciencePolitical scienceMedicineHealth careAlternative medicineEpistemologyLawEngineeringNursing

Abstract

fetched live from OpenAlex

OBJECTIVE: To highlight the emerging ethos of cultural rigour in the use of critical appraisal tools in research involving First Nations peoples. METHODS: Critical reflection on recent systematic review experience. RESULTS: The concept of cultural rigour is notably undefined in peer-reviewed journal articles but is evident in the development of critical appraisal tools developed by First Nations peoples. CONCLUSIONS: Conventional critical appraisal tools for assessing study quality are built on a limited view of health that excludes the cultural knowledge of First Nations peoples. Cultural rigour is an emerging field of activity that epitomises First Nations peoples' diverse cultural knowledge through community participation in all aspects of research. Implications for public health: Critical appraisal tools developed by First Nations peoples are available to researchers and direct attention to the social, cultural, political and human rights basis of health research.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.845
metaresearch head score (Gemma)0.900
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: Methods
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.155
Threshold uncertainty score0.191

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.8450.900
Meta-epidemiology (narrow)0.0040.004
Meta-epidemiology (broad)0.0090.006
Bibliometrics0.0350.020
Science and technology studies0.0100.038
Scholarly communication0.0330.025
Open science0.0090.024
Research integrity0.0100.018
Insufficient payload (model declined to judge)0.0050.002

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.237
GPT teacher head0.486
Teacher spread0.249 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designNot applicable
DomainMethods
GenreMethods

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations17
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueAustralian and New Zealand Journal of Public HealthSame topicIndigenous Health, Education, and RightsFrench-language works237,207